class_docstr: Represents the schema of a dataset with tensor features and targets.
docstr: Deserialize from dictionary representation.
  
  Args:
      schema_dict: Dictionary representation of model signature. Expected dictionary format:
          `{'features': <json string>, 'targets': <json string>" }`
  
  Returns:
      TensorDatasetSchema populated with the data from the dictionary.
docstr_tok: ["Deserialize","from","dictionary","representation",".","Args",":","schema_dict",":","Dictionary","representation","of","model","signature",".","Expected","dictionary","format",":","`","{","'features","'",":","<","json","string",">",",","'targets","'",":","<","json","string",">","''","}","`","Returns",":","TensorDatasetSchema","populated","with","the","data","from","the","dictionary","."]
code: def from_dict(cls, schema_dict: Dict[str, Any]):
      """Deserialize from dictionary representation.
  
      Args:
          schema_dict: Dictionary representation of model signature. Expected dictionary format:
              `{'features': <json string>, 'targets': <json string>" }`
  
      Returns:
          TensorDatasetSchema populated with the data from the dictionary.
  
      """
      if "mlflow_tensorspec" not in schema_dict:
          raise MlflowException(
              "TensorDatasetSchema dictionary is missing expected key 'mlflow_tensorspec'",
              INVALID_PARAMETER_VALUE,
          )
  
      schema_dict = schema_dict["mlflow_tensorspec"]
      features = Schema.from_json(schema_dict["features"])
      if (
          "targets" in schema_dict
          and schema_dict["targets"] is not None
      ):
          targets = Schema.from_json(schema_dict["targets"])
          return cls(features, targets)
      else:
          return cls(features)
  
file_path: mlflow/mlflow/data/schema.py
imports: from typing import Any, Dict
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.types.schema import Schema
label_desc: Use image node_id 3 for calling the TensorDatasetSchema obj's underlying member method code with example usage: obj.from_dict(cls, schema_dict) and returns: cls, cls